Gender Classification of Weblog Authors

Xiang Yan, Ling Yan

In this paper, we present a Naive Bayes classification approach to identify genders of weblog authors. In addition to features employed in traditional text categorization, we use weblog-specific features such as web page background colors and emoticons. Our results in progress, although preliminary, outperform the chosen baseline. They also suggest room for significant improvement once more advanced functionalities of the classifier are implemented.

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